IMK-IFU UHOH IFPRI ISSER WRI. Integrating Governance & Modeling Challenge Program White Volta Basin Sub-Project.

IMK-IFU UHOHIFPRI ISSER WRI

Integrating Integrating Governance & Governance & ModelingModeling

Cha

lleng

e P

rogr

am

White Volta Basin Sub-ProjectWhite Volta Basin Sub-Project

Governance Governance && Modeling Modeling

Cha

lleng

e P

rogr

am

Use cases:Use cases:

In consultation with Ministry of Food and Agriculture and the Water Resources Commission,

Modeling Workshop in Jan. 2006,1. Evaluating third cropping season strategy,

2. Evaluating the impact of Credit Market Reforms,

Governance Governance && Modeling Modeling

Cha

lleng

e P

rogr

am

Modeling:

1. MAS: Optimization component: - New household survey not enough for input-

output estimation,- Started with old Matrix,- Representing the third cropping season (maize)

a challenge:- New proposal and no household level data,- MoFA did experiments but no recorded data,- Alternative CropWat, FAO report and data from case

farmers visited during different survey times.

Governance Governance && Modeling Modeling

Cha

lleng

e P

rogr

am

Table: Irrigation Water Requirement

Units Values Planting date day Feb-15 Irrigation Interval days 10 Irrigation Efficiency % 50 Total Irrigation Requirement M3 per ha 3640

Total Irrigation Requirement lt per ha 3640000

Table: Estimated performance of Barbera Pump in Burkina Faso

Items units Capacity M3 per hr 7.5

Operating labor hrs/day/ha 10.6 Pump Life years 5 Pump+tubes Cost ‘000 Cedis 17000 Depreciation ‘000 Cedis 3400 Maintenance (70 % of depreciation) ‘000 Cedis 2380 Gasoline lt per hr 0.4 oil lt per hr 0.05

Governance Governance && Modeling Modeling

Cha

lleng

e P

rogr

am

Table: Summary of Cost of Pump Irrigation

Items Units Values Pumping qts

Pumping hrs hrs 485.3333 Pumping labor Mds 45.78616

Fuel lt per ha 194.1333 oil lt per ha 24.26667

Pumping Costs Cedis

Labor Cedis/ha 228930.8 Fuel Cedis/ha 1366508 oil Cedis/ha 485333.3

Depreciation Cedis/season 3400000 Maintenance Cedis/season 2380000

Table: Unit Pumping Costs

Units Price Fuel cedis/gallon 32000 Fuel cedis/lt 7039.016 oil cedis/lt 20000

wage cedis/mds 5000 Source: (Jan/Feb 2006 interview)

Governance Governance && Modeling Modeling

Cha

lleng

e P

rogr

am

2. Hydrologic component2. Hydrologic component::

Governance Governance && Modeling Modeling

Cha

lleng

e P

rogr

am

2. Hydrological model:

-WaSiM-ETH Model for Atankwidi subcatchment,

- 12 months modeling period (01.01.2004 to 31.12.2004),

- validation done by one year runoff data “Kandiga Junction”,

- simulation run with a spatial resolution of 100m and a daily temporal resolution,

- the simulation included fictive reservoir and a fictive irrigation field,

Governance Governance && Modeling Modeling

Cha

lleng

e P

rogr

am

Governance Governance && Modeling Modeling

Cha

lleng

e P

rogr

am

Table : Input data for the parameterisation of WaSiM-ETH

H. Ahrends (2005)

Parameter Unit Temporal Resolution

Spatial Resolituion

Acquisition Number of Stations

rainfall mm 1d 8 Global radiation W/m² 1d 2 Relative sunshine fraction

1/1 1d 1

temperature °C 1d 3 relative humidity

% 1d 3

Meteo-rological

Data

Wind speed m/s 1d

Station measurements

3

Land use 100m

Soil Type 100m

Geo-graphical

Data Digital Elevation Model

100m

Field studies & map analysis

Hydro-logical Data

discharge m³/s 1d Discharge

neasurements 1

Governance Governance && Modeling Modeling

Cha

lleng

e P

rogr

am

Spatial Representation of ModelsSpatial Representation of Models

#S#S#S#S#S#S#S#S#S#S

#S#S#S#S#S#S#S

#S#S#S

#S#S#S#S#S#S#S #S#S#S

#S

#S#S#S

#S#S#S#S#S#S#S#S#S

#S#S

#S#S#S#S#S#S#S

#S

#S #S#S#S#S#S#S#S

#S#S#S#S#S#S#S#S#S

#S#S#S#S#S#S#S#S#S

#S#S

#S#S #S#S#S#S#S#S#S#S

#S

#S

#S

#S

#S

#S#S#S

#S#S#S

#S#S

#S#S#S

#S#S#S#S#S

#S

#S

#S#S#S#S#S#S#S#S#S

#S#S #S#S#S

#S#S#S

#S#S #S#S#S#S#S#S#S

#S#S#S

#S#S#S#S

#S#S#S#S#S#S

#S#S#S#S#S#S #S

#S#S

#S#S #S#S#S#S#S#S

#S

#S #S#S#S#S#S#S#S#S

#S

#S#S #S#S#S#S#S#S

#S

#S#S#S#S#S #S#S#S#S#S

#S

#S#S#S#S#S#S#S#S#S#S

#S#S#S#S#S#S#S #S#S#S

#S #S#S#S#S #S#S#S#S#S

#S #S#S#S#S#S #S

#S#S#S

#S#S#S

#S#S#S#S#S

#S#S#S#S#S#S

#S #S#S#S #S#S#S#S

##

#

#

#

# # # ## #

#

#

#

#

#

#

#

#

#

#

#

##

#

#

#

#

#

#

#

#

#

#

#

#

#

#

#

#

#

#

#

#

#

#

#

#

#

#

#

#

#

#

#

#

#

#

#

#

#

##

#

#

#

#

##

#

#

#

#

#

#

#

#

##

# #

#

#

##

#

#

#

#

##

##

# #

##

#

#

#

#

#

#

##

#

#

##

#

#

####

#

#

#

#

#

##

#

#

#

#

#

#

# #

#

#

#

#

#S Clean.shp# Towns_uer.shp

Ue_roads_clip.shpVolta_epp+lin.shp

Integrated Governance and Modeling Survey Sites

Governance Governance && Modeling Modeling

Cha

lleng

e P

rogr

am

- The major challenge we have now is synchronizing the geo-- The major challenge we have now is synchronizing the geo-references of the socio-economic surveys and the references of the socio-economic surveys and the hydrological data. It looks there scaling problem between the hydrological data. It looks there scaling problem between the two. two.

V o lta _ e pp + lin .s h p

1

Governance Governance && Modeling Modeling

Cha

lleng

e P

rogr

am